Collaborative filtering: Techniques and applications
During the last decade a huge amount of data have been shown and introduced in the Internet. Recommender systems are thus predicting the rating that a user would give to an item. Collaborative filtering (CF) techniques are the most popular and widely used by recommender systems technique, which util...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
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2017
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| _version_ | 1796866337366081536 |
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| author | Mustafa, Najdt Ibrahim, Ashraf Osman Ahmed, Ali Abdullah, Afnizanfaizal |
| author_facet | Mustafa, Najdt Ibrahim, Ashraf Osman Ahmed, Ali Abdullah, Afnizanfaizal |
| author_sort | Mustafa, Najdt |
| collection | ePrints |
| description | During the last decade a huge amount of data have been shown and introduced in the Internet. Recommender systems are thus predicting the rating that a user would give to an item. Collaborative filtering (CF) techniques are the most popular and widely used by recommender systems technique, which utilize similar neighbors to generate recommendations. This paper provides the concepts, methods, applications and evaluations of the CF based on the literature review. The paper also highlights the discussion of the types of the recommender systems as general and types of CF such as; memory based, model based and hybrid model. In addition, this paper discusses how to choose an appropriate type of CF. The evaluation methods of the CF systems are also provided throughout the paper. |
| first_indexed | 2024-03-05T21:10:38Z |
| format | Conference or Workshop Item |
| id | utm.eprints-97006 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T21:10:38Z |
| publishDate | 2017 |
| record_format | dspace |
| spelling | utm.eprints-970062022-09-12T04:12:50Z http://eprints.utm.my/97006/ Collaborative filtering: Techniques and applications Mustafa, Najdt Ibrahim, Ashraf Osman Ahmed, Ali Abdullah, Afnizanfaizal QA75 Electronic computers. Computer science During the last decade a huge amount of data have been shown and introduced in the Internet. Recommender systems are thus predicting the rating that a user would give to an item. Collaborative filtering (CF) techniques are the most popular and widely used by recommender systems technique, which utilize similar neighbors to generate recommendations. This paper provides the concepts, methods, applications and evaluations of the CF based on the literature review. The paper also highlights the discussion of the types of the recommender systems as general and types of CF such as; memory based, model based and hybrid model. In addition, this paper discusses how to choose an appropriate type of CF. The evaluation methods of the CF systems are also provided throughout the paper. 2017 Conference or Workshop Item PeerReviewed Mustafa, Najdt and Ibrahim, Ashraf Osman and Ahmed, Ali and Abdullah, Afnizanfaizal (2017) Collaborative filtering: Techniques and applications. In: 2017 International Conference on Communication, Control, Computing and Electronics Engineering, ICCCCEE 2017, 16 - 17 January 2017, Khartoum, Sudan. http://dx.doi.org/10.1109/ICCCCEE.2017.7867668 |
| spellingShingle | QA75 Electronic computers. Computer science Mustafa, Najdt Ibrahim, Ashraf Osman Ahmed, Ali Abdullah, Afnizanfaizal Collaborative filtering: Techniques and applications |
| title | Collaborative filtering: Techniques and applications |
| title_full | Collaborative filtering: Techniques and applications |
| title_fullStr | Collaborative filtering: Techniques and applications |
| title_full_unstemmed | Collaborative filtering: Techniques and applications |
| title_short | Collaborative filtering: Techniques and applications |
| title_sort | collaborative filtering techniques and applications |
| topic | QA75 Electronic computers. Computer science |
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